Begin by examining the data set. Recognize how the data is recorded and how you may be able to use the given data to explore potential relationships between categories.
Scatterplot Questions
1. Create a scatterplot using average MPG and another category that you feel may influence fuel efficiency. Answer the following questions.
Identify the category you chose and why you thought there might be a relationship BEFORE creating the scatterplot?
Answer: MPG and horsepower due to more engine = more fuel
Create the scatterplot. Which category is your x-axis and which is your y-axis? Why did you create your scatterplot in that order?
Answer:X-Axis was MPG and Y-axis was Horsepower. It was just easier to do it in this order
Do you believe there is a relationship between the two categories? Why or why not?
Answer:
If there appears to be a relationship, does it have a positive or negative slope? What does this mean about the relationship between the two categories?
Answer: Negative slope as one increases the other decreases
Create the linear regession equation in Excel, which Excel calls the trend line. Click the boxes to create both the equation and the r2 value on the graph. Answer the following questions.
What is your regression equation? Explain what the equation means in words.
Answer: y = -6.326 X + 307.5
What is your r2 value? Is this a strong correlation? Why or Why not? If you are not sure, try searching the internet for supporting documents. Provide URL's for where you find your information
Answer: r-squared value is .430 This is considered a weak linear relationship
Based on all the information you have, has your belief about the relationship of the two categories changes? Why or why not?
Answer: The relationship is not linear.
Analysis
Right click on the regression equation and select "Format Trendline". Explore the different variations of regression equations.
How would you determine which equation had the best relationship?
Answer: Check the r-squared value. The closer to 1 the better
Was the "Linear" option the optimal option? If so, why? If not, what was the better equation and why?
Answer: no, the exponential decay had a .547 R-squared value and the power graph had a .563 R-Squared value
Attach your Scatter Plots and Regression Information. Make sure your X and Y axis are correctly labeled. You may use Screen Shots to do so.
Begin by examining the data set. Recognize how the data is recorded and how you may be able to use the given data to explore potential relationships between categories.
Scatterplot Questions
1. Create a scatterplot using average MPG and another category that you feel may influence fuel efficiency. Answer the following questions.
Answer: MPG and horsepower due to more engine = more fuelIdentify the category you chose and why you thought there might be a relationship BEFORE creating the scatterplot?
Answer:X-Axis was MPG and Y-axis was Horsepower. It was just easier to do it in this orderCreate the scatterplot. Which category is your x-axis and which is your y-axis? Why did you create your scatterplot in that order?
Answer:Do you believe there is a relationship between the two categories? Why or why not?
Answer: Negative slope as one increases the other decreasesIf there appears to be a relationship, does it have a positive or negative slope? What does this mean about the relationship between the two categories?
Regression Questions
(What is Regression?)
Create the linear regession equation in Excel, which Excel calls the trend line. Click the boxes to create both the equation and the r2 value on the graph. Answer the following questions.
Answer: y = -6.326 X + 307.5What is your regression equation? Explain what the equation means in words.
Answer: r-squared value is .430 This is considered a weak linear relationshipWhat is your r2 value? Is this a strong correlation? Why or Why not? If you are not sure, try searching the internet for supporting documents. Provide URL's for where you find your information
Answer: The relationship is not linear.Based on all the information you have, has your belief about the relationship of the two categories changes? Why or why not?
Analysis
Right click on the regression equation and select "Format Trendline". Explore the different variations of regression equations.
Answer: Check the r-squared value. The closer to 1 the betterHow would you determine which equation had the best relationship?
Answer: no, the exponential decay had a .547 R-squared value and the power graph had a .563 R-Squared valueWas the "Linear" option the optimal option? If so, why? If not, what was the better equation and why?
Attach your Scatter Plots and Regression Information. Make sure your X and Y axis are correctly labeled. You may use Screen Shots to do so.